Recognition of Isolated Complex Mono- and Bi-Manual 3D Hand Gestures
In this paper, we address the problem of the recognition of isolated complex mono- and bi-manual hand gestures. In the proposed system, hand gestures are represented by the 3D trajectories of blobs. Blobs are obtained by tracking colored body parts in real-time using the EM algorithm. In most of the studies on hand gestures, only small vocabularies have been used. In this paper, we study the results obtained on a more complex database of mono- and bi-manual gestures. These results are obtained by using a state-of-the-art sequence processing algorithm, namely Hidden Markov Models (HMMs), implemented within the framework of an open source machine learning library.
Published in "Proceedings of the sixth International Conference on Automatic Face and Gesture Recognition", 2004
Record created on 2006-03-10, modified on 2016-08-08